944 resultados para maximum likelihood method


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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

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Accurate estimates of the penetrance rate of autosomal dominant conditions are important, among other issues, for optimizing recurrence risks in genetic counseling. The present work on penetrance rate estimation from pedigree data considers the following situations: 1) estimation of the penetrance rate K (brief review of the method); 2) construction of exact credible intervals for K estimates; 3) specificity and heterogeneity issues; 4) penetrance rate estimates obtained through molecular testing of families; 5) lack of information about the phenotype of the pedigree generator; 6) genealogies containing grouped parent-offspring information; 7) ascertainment issues responsible for the inflation of K estimates.

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A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.

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This thesis is the result of my experience as a PhD student taking part in the Joint Doctoral Programme at the University of York and the University of Bologna. In my thesis I deal with topics that are of particular interest in Italy and in Great Britain. Chapter 2 focuses on the empirical test of the existence of the relationship between technological profiles and market structure claimed by Sutton’s theory (1991, 1998) in the specific economic framework of hospital care services provided by the Italian National Health Service (NHS). In order to test the empirical predictions by Sutton, we identify the relevant markets for hospital care services in Italy in terms of both product and geographic dimensions. In particular, the Elzinga and Hogarty (1978) approach has been applied to data on patients’ flows across Italian Provinces in order to derive the geographic dimension of each market. Our results provide evidence in favour of the empirical predictions of Sutton. Chapter 3 deals with the patient mobility in the Italian NHS. To analyse the determinants of patient mobility across Local Health Authorities, we estimate gravity equations in multiplicative form using a Poisson pseudo maximum likelihood method, as proposed by Santos-Silva and Tenreyro (2006). In particular, we focus on the scale effect played by the size of the pool of enrolees. In most of the cases our results are consistent with the predictions of the gravity model. Chapter 4 considers the effects of contractual and working conditions on selfassessed health and psychological well-being (derived from the General Health Questionnaire) using the British Household Panel Survey (BHPS). We consider two branches of the literature. One suggests that “atypical” contractual conditions have a significant impact on health while the other suggests that health is damaged by adverse working conditions. The main objective of our paper is to combine the two branches of the literature to assess the distinct effects of contractual and working conditions on health. The results suggest that both sets of conditions have some influence on health and psychological well-being of employees.

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Das Standardmodell (SM) der Teilchenphysik beschreibt sehr präzise die fundamentalen Bausteine und deren Wechselwirkungen (WW). Trotz des Erfolges gibt es noch offene Fragen, die vom SM nicht beantwortet werden können. Ein noch noch nicht abgeschlossener Test besteht aus der Messung der Stärke der schwachen Kopplung zwischen Quarks. Neutrale B- bzw. $bar{B}$-Mesonen können sich innerhalb ihrer Lebensdauer über einen Prozeß der schwachen WW in ihr Antiteilchen transformieren. Durch die Messung der Bs-Oszillation kann die Kopplung Vtd zwischen den Quarksorten Top (t) und Down (d) bestimmt werden. Alle bis Ende 2005 durchgeführten Experimente lieferten lediglich eine untere Grenze für die Oszillationsfrequenz von ms>14,4ps-1. Die vorliegenden Arbeit beschreibt die Messung der Bs-Oszillationsfrequenz ms mit dem semileptonischen Kanal BsD(-)+. Die verwendeten Daten stammen aus Proton-Antiproton-Kollisionen, die im Zeitraum von April 2002 bis März 2006 mit dem DØ-Detektor am Tevatron-Beschleuniger des Fermi National Accelerator Laboratory bei einer Schwerpunktsenergie von $sqrt{s}$=1,96TeV aufgezeichnet wurden. Die verwendeten Datensätze entsprechen einer integrierten Luminosität von 1,3fb-1 (620 millionen Ereignisse). Für diese Oszillationsmessung wurde der Quarkinhalt des Bs-Mesons zur Zeit der Produktion sowie des Zerfalls bestimmt und die Zerfallszeit wurde gemessen. Nach der Rekonstruktion und Selektion der Signalereignisse legt die Ladung des Myons den Quarkinhalt des Bs-Mesons zur Zeit des Zerfalls fest. Zusätzlich wurde der Quarkinhalt des Bs-Mesons zur Zeit der Produktion markiert. b-Quarks werden in $pbar{p}$-Kollisionen paarweise produziert. Die Zerfallsprodukte des zweiten b-Hadrons legen den Quarkinhalt des Bs-Mesons zur Zeit der Produktion fest. Bei einer Sensitivität von msenss=14,5ps-1 wurde eine untere Grenze für die Oszillationsfrequenz ms>15,5ps-1 bestimmt. Die Maximum-Likelihood-Methode lieferte eine Oszillationsfrequenz ms>(20+2,5-3,0(stat+syst)0,8(syst,k))ps-1 bei einem Vertrauensniveau von 90%. Der nicht nachgewiesene Neutrinoimpuls führt zu dem systematischen Fehler (sys,k). Dieses Resultat ergibt zusammen mit der entsprechenden Oszillation des Bd-Mesons eine signifikante Messung der Kopplung Vtd, in Übereinstimmung mit weiteren Experimenten über die schwachen Quarkkopplungen.

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Background Pelvic inflammatory disease (PID) results from the ascending spread of microorganisms from the vagina and endocervix to the upper genital tract. PID can lead to infertility, ectopic pregnancy and chronic pelvic pain. The timing of development of PID after the sexually transmitted bacterial infection Chlamydia trachomatis (chlamydia) might affect the impact of screening interventions, but is currently unknown. This study investigates three hypothetical processes for the timing of progression: at the start, at the end, or throughout the duration of chlamydia infection. Methods We develop a compartmental model that describes the trial structure of a published randomised controlled trial (RCT) and allows each of the three processes to be examined using the same model structure. The RCT estimated the effect of a single chlamydia screening test on the cumulative incidence of PID up to one year later. The fraction of chlamydia infected women who progress to PID is obtained for each hypothetical process by the maximum likelihood method using the results of the RCT. Results The predicted cumulative incidence of PID cases from all causes after one year depends on the fraction of chlamydia infected women that progresses to PID and on the type of progression. Progression at a constant rate from a chlamydia infection to PID or at the end of the infection was compatible with the findings of the RCT. The corresponding estimated fraction of chlamydia infected women that develops PID is 10% (95% confidence interval 7-13%) in both processes. Conclusions The findings of this study suggest that clinical PID can occur throughout the course of a chlamydia infection, which will leave a window of opportunity for screening to prevent PID.

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BACKGROUND Blood pressure (BP) is known to aggregate in families. Yet, heritability estimates are population-specific and no Swiss data have been published so far. We estimated the heritability of ambulatory and office BP in a Swiss population-based sample. METHODS The Swiss Kidney Project on Genes in Hypertension is a population-based family study focusing on BP genetics. Office and ambulatory BP were measured in 1009 individuals from 271 nuclear families. Heritability was estimated for SBP, DBP, and pulse pressure using a maximum likelihood method implanted in the Statistical Analysis in Genetic Epidemiology software. RESULTS The 518 women and 491 men included in this analysis had a mean (±SD) age of 48.3 (±17.4) and 47.3 (±17.7) years, and a mean BMI of 23.8 (±4.2) and 25.9 (±4.1) kg/m, respectively. Narrow-sense heritability estimates (±standard error) for ambulatory SBP, DBP, and pulse pressure were 0.37 ± 0.07, 0.26 ± 0.07, and 0.29 ± 0.07 for 24-h BP; 0.39 ± 0.07, 0.28 ± 0.07, and 0.27 ± 0.07 for day BP; and 0.25 ± 0.07, 0.20 ± 0.07, and 0.30 ± 0.07 for night BP, respectively (all P < 0.001). Heritability estimates for office SBP, DBP, and pulse pressure were 0.21 ± 0.08, 0.25 ± 0.08, and 0.18 ± 0.07 (all P < 0.01). CONCLUSIONS We found significant heritability estimates for both ambulatory and office BP in this Swiss population-based study. Our findings justify the ongoing search for the genetic determinants of BP.

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This study investigates a theoretical model where a longitudinal process, that is a stationary Markov-Chain, and a Weibull survival process share a bivariate random effect. Furthermore, a Quality-of-Life adjusted survival is calculated as the weighted sum of survival time. Theoretical values of population mean adjusted survival of the described model are computed numerically. The parameters of the bivariate random effect do significantly affect theoretical values of population mean. Maximum-Likelihood and Bayesian methods are applied on simulated data to estimate the model parameters. Based on the parameter estimates, predicated population mean adjusted survival can then be calculated numerically and compared with the theoretical values. Bayesian method and Maximum-Likelihood method provide parameter estimations and population mean prediction with comparable accuracy; however Bayesian method suffers from poor convergence due to autocorrelation and inter-variable correlation. ^

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Ordinal outcomes are frequently employed in diagnosis and clinical trials. Clinical trials of Alzheimer's disease (AD) treatments are a case in point using the status of mild, moderate or severe disease as outcome measures. As in many other outcome oriented studies, the disease status may be misclassified. This study estimates the extent of misclassification in an ordinal outcome such as disease status. Also, this study estimates the extent of misclassification of a predictor variable such as genotype status. An ordinal logistic regression model is commonly used to model the relationship between disease status, the effect of treatment, and other predictive factors. A simulation study was done. First, data based on a set of hypothetical parameters and hypothetical rates of misclassification was created. Next, the maximum likelihood method was employed to generate likelihood equations accounting for misclassification. The Nelder-Mead Simplex method was used to solve for the misclassification and model parameters. Finally, this method was applied to an AD dataset to detect the amount of misclassification present. The estimates of the ordinal regression model parameters were close to the hypothetical parameters. β1 was hypothesized at 0.50 and the mean estimate was 0.488, β2 was hypothesized at 0.04 and the mean of the estimates was 0.04. Although the estimates for the rates of misclassification of X1 were not as close as β1 and β2, they validate this method. X 1 0-1 misclassification was hypothesized as 2.98% and the mean of the simulated estimates was 1.54% and, in the best case, the misclassification of k from high to medium was hypothesized at 4.87% and had a sample mean of 3.62%. In the AD dataset, the estimate for the odds ratio of X 1 of having both copies of the APOE 4 allele changed from an estimate of 1.377 to an estimate 1.418, demonstrating that the estimates of the odds ratio changed when the analysis includes adjustment for misclassification. ^

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Many public health agencies and researchers are interested in comparing hospital outcomes, for example, morbidity, mortality, and hospitalization across areas and hospitals. However, since there is variation of rates in clinical trials among hospitals because of several biases, we are interested in controlling for the bias and assessing real differences in clinical practices. In this study, we compared the variations between hospitals in rates of severe Intraventricular Haemorrhage (IVH) infant using Frequentist statistical approach vs. Bayesian hierarchical model through simulation study. The template data set for simulation study was included the number of severe IVH infants of 24 intensive care units in Australian and New Zealand Neonatal Network from 1995 to 1997 in severe IVH rate in preterm babies. We evaluated the rates of severe IVH for 24 hospitals with two hierarchical models in Bayesian approach comparing their performances with the shrunken rates in Frequentist method. Gamma-Poisson (BGP) and Beta-Binomial (BBB) were introduced into Bayesian model and the shrunken estimator of Gamma-Poisson (FGP) hierarchical model using maximum likelihood method were calculated as Frequentist approach. To simulate data, the total number of infants in each hospital was kept and we analyzed the simulated data for both Bayesian and Frequentist models with two true parameters for severe IVH rate. One was the observed rate and the other was the expected severe IVH rate by adjusting for five predictors variables for the template data. The bias in the rate of severe IVH infant estimated by both models showed that Bayesian models gave less variable estimates than Frequentist model. We also discussed and compared the results from three models to examine the variation in rate of severe IVH by 20th centile rates and avoidable number of severe IVH cases. ^

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Operational Modal Analysis consists on estimate the modal parameters of a structure (natural frequencies, damping ratios and modal vectors) from output-only vibration measurements. The modal vectors can be only estimated where a sensor is placed, so when the number of available sensors is lower than the number of tested points, it is usual to perform several tests changing the position of the sensors from one test to the following (multiple setups of sensors): some sensors stay at the same position from setup to setup, and the other sensors change the position until all the tested points are covered. The permanent sensors are then used to merge the mode shape estimated at each setup (or partial modal vectors) into global modal vectors. Traditionally, the partial modal vectors are estimated independently setup by setup, and the global modal vectors are obtained in a postprocess phase. In this work we present two state space models that can be used to process all the recorded setups at the same time, and we also present how these models can be estimated using the maximum likelihood method. The result is that the global mode shape of each mode is obtained automatically, and subsequently, a single value for the natural frequency and damping ratio of the mode is computed. Finally, both models are compared using real measured data.